grandes-ecoles 2020 Q35

grandes-ecoles · France · centrale-maths2__official Continuous Probability Distributions and Random Variables Verification of Probability Measure or Inner Product Properties

Let $(E, \langle \cdot, \cdot \rangle)$ be a reproducing kernel Hilbert space on an interval $I$, with reproducing kernel $K$. For all $(x,y) \in I^2$, we set $k_x(y) = K(x,y)$. Let $x \in I$ and $V_x$ defined on $E$ by $V_x(f) = f(x)$. We set $$N(V_x) = \sup_{\|f\|=1} |f(x)|$$ Prove that $$N(V_x) = \sqrt{\langle k_x, k_x \rangle}.$$

Let $(E, \langle \cdot, \cdot \rangle)$ be a reproducing kernel Hilbert space on an interval $I$, with reproducing kernel $K$. For all $(x,y) \in I^2$, we set $k_x(y) = K(x,y)$.\\
Let $x \in I$ and $V_x$ defined on $E$ by $V_x(f) = f(x)$. We set
$$N(V_x) = \sup_{\|f\|=1} |f(x)|$$
Prove that
$$N(V_x) = \sqrt{\langle k_x, k_x \rangle}.$$

Paper Questions

Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22 Q23 Q24 Q25 Q26 Q27 Q28 Q29 Q30 Q31 Q32 Q33 Q34 Q35 Q36 Q37 Q38